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This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

# resource_allocation_index¶

Compute the resource allocation index of all node pairs in ebunch.

Resource allocation index of $$u$$ and $$v$$ is defined as

$\sum_{w \in \Gamma(u) \cap \Gamma(v)} \frac{1}{|\Gamma(w)|}$

where $$\Gamma(u)$$ denotes the set of neighbors of $$u$$.

Parameters : G : graph A NetworkX undirected graph. ebunch : iterable of node pairs, optional (default = None) Resource allocation index will be computed for each pair of nodes given in the iterable. The pairs must be given as 2-tuples (u, v) where u and v are nodes in the graph. If ebunch is None then all non-existent edges in the graph will be used. Default value: None. piter : iterator An iterator of 3-tuples in the form (u, v, p) where (u, v) is a pair of nodes and p is their resource allocation index.

References

 [R266] T. Zhou, L. Lu, Y.-C. Zhang. Predicting missing links via local information. Eur. Phys. J. B 71 (2009) 623. http://arxiv.org/pdf/0901.0553.pdf

Examples

>>> import networkx as nx
>>> G = nx.complete_graph(5)
>>> preds = nx.resource_allocation_index(G, [(0, 1), (2, 3)])
>>> for u, v, p in preds:
...     '(%d, %d) -> %.8f' % (u, v, p)
...
'(0, 1) -> 0.75000000'
'(2, 3) -> 0.75000000'